Virtual musician learns any playing style

PORTLAND, Ore.  By learning the melodic, harmonic and rhythmic features of any musical style, a virtual musician called iMe is being billed as the world's first intelligent musical instrument capable of playing along with any soloist.

Developed at the Interdisciplinary Center for Computer Music Research at the University of Plymouth (U.K.), iMe can jam with real musicians by learning their style, or by mimicking the style of any musician from their recorded scores. The iMe program will be made available as open-source shareware.

"IMe uses a machine learning paradigm called data-driven learning," said Eduardo Miranda, a professor at the center. "It doesn't just look at the individual notes, but identifies sequences of features--it's a multidimensional representation of music."

The tool was crafted by doctoral candidate Marcelo Gimenes as a virtual musician that can accompany musicians when they play live. It tracks the note sequences being played, identifies their style, then responds with complementary improvisations in the same style.

According to Miranda, iMe takes only a few songs to identify a musician's style. It works by creating its own knowledge base of musical phrases as it listens to examples. After the learning period, which requires only a few examples before its pegs a musical style, according to Miranda, the program can improvise along with the live musician as they play.

"As you input musical notes, the program segments the information and builds tables with probabilities among various parameters of the music," said Miranda. It then "builds its own knowledge for the sequences."

Musical note sequences are segmented into phrases that are defined by competing sets of rules not all of which apply to each type of musical style, but some of which apply to every style of music. In this way, regardless of musical style, the program will identify salient features and adapt its responses to them.

It also follows several sets of rules in parallel. For instance, it identifies whether a melody of notes is going up or down, whether the interval between the notes is wide or short, whether a sequence of closely spaced notes is ended by a large interval then started up again with closely spaced notes moving in the opposite direction, what are the prevailing chords during each time interval and whether chord changes are following a common harmonic progression.

"IMe applies melodic, harmonic and rythmic rule sets that allow the segmenting of note sequences into phrases," said Miranda. "The rule sets compete with each other, so the system is always looking for better ways of interpreting them."